With the aid of modern imaging methods, two or three-dimensional image data is often created which can be used for visualizing an imaged examination object and also for further uses.
Frequently, the imaging methods are based on the detection of X-ray radiation, wherein “projection scan data” is generated. For example, projection scan data can be acquired with the aid of a computed tomography (CT) system. In CT systems, typically a combination of an X-ray source and an oppositely arranged X-ray detector mounted on a gantry run round a measurement space in which the examination object (which in the following is designated “patient” without any restriction of the generality) is situated. The center of rotation (also known as “isocenter”) coincides with a “system axis” z. During one or two rotations, the patient is irradiated with X-ray radiation from the X-ray source, wherein projection scan data or X-ray projection data is acquired with the aid of the X-ray detector positioned opposite thereto.
The projection scan data generated is dependent particularly on the construction of the X-ray detector. X-ray detectors typically have a plurality of detector units which are usually arranged in a regular pixel array. The detector units each generate, for X-ray radiation falling on the detector units, a detector signal which is analyzed at particular time points with regard to intensity and spectral distribution of the X-ray radiation in order to draw conclusions about the examination object and to generate projection scan data.
With the aid of CT imaging, for a long time it has “only” been possible to image anatomical structures. Functional imaging via computed tomography was for a long time not possible, however, partially because of an excessive radiation loading on the patient. In the last few years, however, due to technological progress, the possibilities for functional imaging have improved and they have found their way into clinical routine. However, the search for functional measuring variables continues and one of these has been sought after for a particularly long time: the measurement of flow velocity in blood vessels.
In the first place, knowledge of blood flow velocities can help to find and/or characterize pathologies (e.g. stenoses). Secondly, it enables optimization of the acquisition parameters for CT scans supported by contrast medium, for example, angiography scans. The determination of the blood flow velocity is already possible with medical measuring methods such as magnetic resonance tomography (MRT) and ultrasound (US). When determining the blood flow velocity with the aid of magnetic resonance tomography, body tissues can be brought via magnetic fields into a particular electromagnetic state. From the change in magnetization, for example, via the blood flow, the velocity of the blood is determined (using “Magnetic Resonance Velocimetry”). Contrast media are not always needed for this method.
When determining the blood flow rate with the aid of an ultrasonic method, however, the Doppler effect is used, wherein via the frequency shift in the sound waves, it is revealed how high the blood flow velocity is. With this method also, no contrast medium is needed and, in a similar way, there are also optical methods (e.g. with a laser) to measure the blood flow velocity using the Doppler effect.
For CT imaging methods, there are several patented methods for measuring blood flow velocity, as described for example, in the following scientific publications and patent applications: a first method comprises a process wherein from the time offset of the individual projections on the detector, the blood flow velocity during a contrast medium-supported scan is to be determined. This method is described in Prevrhal, S. et al., “CT angiographic measurement of vascular blood flow velocity by using projection data”, Radiology 2011; 261: 923-929 and in the patent application US 2011/0274333 A1.
A second method also comprises a process wherein from the time offset of the individual projections on the detector, the blood flow velocity during a contrast medium-supported scan is to be determined. In this method, as in the first method, it is only projection data or sinograms that are used, but not image data. This second method is described in J J Barfett et al., “Intra-vascular blood velocity and volumetric flow rate calculated from dynamic 4D CT angiography using a time of flight technique”, Int J Cardiovasc Imaging 2014, DOI:10.1007/s10554-014-0471-3 and in US 2013/0172734 A1.
A third method has essentially the same approach as the first and the second methods, although it is supported on the processing of image data in place of projection data. This third method is described in the patent application US 2009/0086882 A1. In the third method, acquisitions take place parallel to the z-axis at different discrete time points. In this regard, the z-axis should be understood to be the virtual axis, also known as the system axis, about which the scanning system rotates. These acquisitions are carried out as repeated sequence scans with a broad collimation. Therefrom, spatial gradients can be derived at the different acquisition times. Similarly, temporal gradients Gt can also be derived at fixed z-positions.
Furthermore, the acquisition is restricted by the maximum coverage of the detector in the z-direction. The blood flow velocity dz/dt is then calculated from the displacement of the spatial gradients.